Modern spectrophotometers are providing greatly enhanced performance in terms of speed and accuracy by means of digital processing of the spectral data. A typical purpose is to provide a comparison of one spectrum with another spectrum or with each spectrum of a set of other spectra. For example, a sample being tested with the spectrophotometer may supposedly be known, and it is desired to compare its spectrum with that of the known material to determine whether the supposition is correct or the sample contains impurities. Another purpose is to compare the sample spectrum with a library of spectra stored in the data station or on a disk that can be addressed. Comparisons may be made by visual observations of the spectra as taught in U.S. Pat. No. 4,560,275 (Goetz), but this method is not always sufficiently accurate nor is it quantitative.
The most common purpose of infrared spectral searching is to match the spectrum of a material to be identified with a spectrum in a library. Various techniques, including peak matching, peakintensity matching, correlation coefficient, Euclidean distance matching, and factor analysis have been applied to spectral searching in order to rapidly compare and rank comparisons of a spectrum to relatively large data sets or libraries. The use of a correlation coefficient is described in an article "Computer Retrieval of Infrared Spectra by a Correlation Coefficient Method" by K. Tanabe and S. Saeki, Analytical Chemistry 47, 118-122 (Jan. 1975).
Several problem phenomena interfere with accuracy of the comparison. These include random noise, instrumental artifacts such as electronic spikes, and drift from temperature changes. A further problem associated with the noise is detecting small differences between overlapping peaks. Filtering of spectra by computer algorithm is disclosed, for example, in an article "Digital Filter for Computationally Efficient Smoothing of Noisy Spectra" by M. U. A. Bromba and H. Ziegler, Analytical Chemistry 55, 1299-1302 (1983). Comparisons may be made on such filtered or smoothed spectra such as by subtracting data as disclosed in U.S. Pat. No. 4,365,303 (Hannah et al). However, it has been found that simple one-step filtering before comparing can be insufficient to reliably distinguish close spectra. Other examples of processing spectral data are found in U.S. Pat. No. 4,238,830 (Unvala).
Therefore, objects of the present invention include improved resolution in the treatment of spectral signals to provide an accurate comparison of spectra.